IEEE Transactions on Automatic Control

最新文章

• Safety-Critical Learning of Robot Control With Temporal Logic Specifications AI翻译
  作者：Cai, Mingyu; Vasile, Cristian-Ioan
  作者单位：University of California System; University of California Riverside; Lehigh University
  摘要：Reinforcement learning (RL) is a promising control approach in many scenarios. However, safety-critical applications are still a challenge due to lack of safety guarantees during exploration and subsequent deployment. The learning problem becomes even more difficult for complex tasks with temporal and logical constraints. In this article, we introduce a modular deep RL architecture as a control framework to satisfy complex tasks specified using linear temporal logic (LTL). To enhance safety, w...
• Cooperative Trajectory Tracking of Heterogeneous Networks by Distributed Learning AI翻译
  作者：Meng, Deyuan; Zhang, Jingyao
  作者单位：Beihang University; Beihang University
  摘要：This article presents a distributed learning approach to achieve the high-precision cooperative trajectory tracking tasks for heterogeneous networks at all time in the presence of changing topologies. An updating law of distributed learning is proposed by leveraging the cooperative tracking error trajectories of agents at all time samples, thanks to which a monotonic convergence result is established for heterogeneous networks of linear agents without iteration-varying uncertainties. When cons...
• Self-Triggered Stabilization of Contracting Systems Under Quantization AI翻译
  作者：Wakaiki, Masashi
  作者单位：Kobe University
  摘要：We propose self-triggered control schemes for nonlinear systems with quantized state measurements. Our focus lies on scenarios where both the controller and the self-triggering mechanism receive only the quantized state at each sampling time. We assume that the ideal closed-loop system without quantization or self-triggered sampling is contracting. Moreover, an upper bound on the growth rate of the open-loop system is assumed to be known. We present two control schemes that achieve closed-loop...
• Multistep Sensor Attackability in Cyber-Physical Systems AI翻译
  作者：Duo, Wenli; Wang, Shouguang; Zhou, MengChu
  作者单位：Macau University of Science & Technology; Zhejiang Gongshang University; New Jersey Institute of Technology
  摘要：This work investigates cyber-attacks targeting cyber-physical systems in the framework of discrete event systems. From intruders' perspective, we propose a concept called k-step attackability to explore attack scenarios where intruders are constrained by a limited number of attack operations. In particular, we focus on a class of sensor attacks where sensor readings can be replaced, deleted, and inserted during transmission. We examine k-step attackability under such attacks and address its ve...
• Completely Stealthy and Energy-Stealthy Sensor Attacks With Constrained Channels: Existence and Design AI翻译
  作者：Jin, Kaijing; Ye, Dan; Zhang, Tian-Yu
  作者单位：Northeastern University - China; Northeastern University - China
  摘要：In this article, the security of state estimation is studied under stealthy false-data injection attacks launched in the sensor-to-estimator channels. It is proved that there is no strictly stealthy sensor attack such that the state estimation is insecure. Thus, we focus on the existence of the attacks with complete and energy stealthiness to gradually remove the attack impact on detectors. Since the existence of stealthy attacks is significantly affected by accessing attack channels, the nece...
• A Perron-Frobenius Theorem for Strongly Aperiodic Stochastic Chains AI翻译
  作者：Parasnis, Rohit; Franceschetti, Massimo; Touri, Behrouz
  作者单位：University of California System; University of California San Diego
  摘要：We derive a generalization of the Perron-Frobenius theorem to time-varying row-stochastic matrices as follows: using Kolmogorov's concept of absolute probability sequences, which are time-varying analogs of principal eigenvectors, we identify a set of connectivity conditions that generalize the notion of irreducibility (strong connectivity) to time-varying matrices (networks), and we show that under these conditions, the absolute probability sequence associated with a given matrix sequence is ...
• Gradient Descent-Based Adaptive Control for Time-Varying Command Following AI翻译
  作者：Jaramillo, Jesse; Yucelen, Tansel
  作者单位：State University System of Florida; University of South Florida; State University System of Florida; University of South Florida
  摘要：Output regulation theory is an effective method for achieving accurate time-varying command following and can utilize adaptive internal models to follow arbitrary reference signals generated by an exosystem. However, implementing these models can still lead to complexities, particularly regarding increased controller order and the dimensionality of gain matrices. This article contributes a gradient descent-based adaptive control method for uncertain dynamical systems. This method offers an alt...
• Optimal Output Feedback Learning Control for Continuous-Time Linear Quadratic Regulation AI翻译
  作者：Xie, Kedi; Guay, Martin; Lu, Maobin; Wang, Shimin; Deng, Fang
  作者单位：Beijing Institute of Technology; Beijing Institute of Technology; Queens University - Canada
  摘要：The classical linear quadratic regulation (LQR) problem of linear systems by state feedback has been widely addressed. However, the LQR problem by dynamic output feedback with optimal transient performance remains open. The main reason is that the observer error inevitably leads to suboptimal transient performance of the closed-loop system. In this article, we propose an optimal dynamic output feedback learning control approach to solve the LQR problem of linear continuous-time systems with un...
• Nonlinear Integral Sliding Mode Control Design for Singularly Perturbed Systems Under Matched and Unmatched Uncertainties AI翻译
  作者：Banza, Arnold Tshimanga; Mareels, Iven
  作者单位：University of Melbourne; Federation University Australia; University of Melbourne
  摘要：A new nonlinear integral sliding mode control (ISMC) algorithm for singularly perturbed multiple-inputs and multiple-outputs (MIMO) systems subject to matched and unmatched uncertainties is proposed. The circumstance of fast sensor dynamics in series with the plant exemplifies the results. Using prior knowledge about the sensor dynamics, the ISMC structure and its parameters can be tuned to ensure that the closed loop converges to a suitably small neighborhood of the desired equilibrium. It is...
• A Semialgebraic Framework for Verification and Synthesis of Control Barrier Functions AI翻译
  作者：Clark, Andrew
  作者单位：Washington University (WUSTL)
  摘要：Safety is a critical property for control systems in medicine, transportation, manufacturing, and other applications, and can be defined as ensuring positive invariance of a predefined safe set. This article investigates the problems of verifying positive invariance of a semialgebraic set as well as synthesizing sets that can be made positive invariant through control barrier function (CBF)-based control. The key to our approach consists of mapping conditions for positive invariance to sum-of-...